yangXinFeng / high_noise_clustering

Techniques to cluster very noisy data (dropouts or random noise)

How to cluster datasets with important levels of noise or dropouts?

Let's start by defining the difference between noise and dropout:

Dropout = dataset non 0 values appear as 0 (single cell RNA-seq data)
Noise = the actual measured values have a certain additional noise (due to sensor calibration, experimental setup, etc)

This repository attempts to:

• explain the theoretical notions behing spectral clustering and self tuned spectral clustering
• implement the affinity matrix computation for self tuned spectral clustering
• implement the eigenvalue gap heuristic for finding the optimal number of clusters